1,328 research outputs found
Perturbation expansions for a class of singular potentials
Harrell's modified perturbation theory [Ann. Phys. 105, 379-406 (1977)] is
applied and extended to obtain non-power perturbation expansions for a class of
singular Hamiltonians H = -D^2 + x^2 + A/x^2 + lambda/x^alpha, (A\geq 0, alpha
> 2), known as generalized spiked harmonic oscillators. The perturbation
expansions developed here are valid for small values of the coupling lambda >
0, and they extend the results which Harrell obtained for the spiked harmonic
oscillator A = 0. Formulas for the the excited-states are also developed.Comment: 23 page
Variational analysis for a generalized spiked harmonic oscillator
A variational analysis is presented for the generalized spiked harmonic
oscillator Hamiltonian operator H, where H = -(d/dx)^2 + Bx^2+ A/x^2 +
lambda/x^alpha, and alpha and lambda are real positive parameters. The
formalism makes use of a basis provided by exact solutions of Schroedinger's
equation for the Gol'dman and Krivchenkov Hamiltonian (alpha = 2), and the
corresponding matrix elements that were previously found. For all the discrete
eigenvalues the method provides bounds which improve as the dimension of the
basis set is increased. Extension to the N-dimensional case in arbitrary
angular-momentum subspaces is also presented. By minimizing over the free
parameter A, we are able to reduce substantially the number of basis functions
needed for a given accuracy.Comment: 15 pages, 1 figur
First Multicharged Ion Irradiation Results from the CUEBIT Facility at Clemson University
A new electron beam ion trap (EBIT) based ion source and beamline were recently commissioned at Clemson University to produce decelerated beams of multi- to highly-charged ions for surface and materials physics research. This user facility is the first installation of a DREEBIT-designedsuperconducting trap and ion source (EBIS-SC) in the U.S. and includes custom-designed target preparation and irradiation setups. An overview of the source, beamline, and other facilities as well as results from first measurements on irradiated targets are discussed here. Results include extracted charge state distributions and first data on a series of irradiated metal-oxide-semiconductor (MOS) device targets. For the MOS devices, we show that voltage-dependent capacitance can serve as a record of theelectronic component of ion stopping power for an irradiated, encapsulated oxide target
Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study
Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model.
Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained.
Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches.
Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR
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Mitigation of Moral Hazard and Adverse Selection in Venture Capital Financing: The Influence of the Country’s Institutional Setting
A venture capitalist (VC) needs to trade off benefits and costs when attempting to mitigate agency problems in their investor-investee relationship. We argue that signals of ventures complement the VC’s capacity to screen and conduct a due diligence during the pre-investment phase, but its attractiveness may diminish in institutional settings supporting greater transparency. Similarly, whereas a VC may opt for contractual covenants to curb potential opportunism by ventures in the post-investment phase, this may only be effective in settings supportive of shareholder rights enforcement. Using an international sample of VC contracts, our study finds broad support for these conjectures. It delineates theoretical and practical implications for how investors can best deploy their capital in different institutional settings whilst nurturing their relationships with entrepreneurs
Understanding the Random Displacement Model: From Ground-State Properties to Localization
We give a detailed survey of results obtained in the most recent half decade
which led to a deeper understanding of the random displacement model, a model
of a random Schr\"odinger operator which describes the quantum mechanics of an
electron in a structurally disordered medium. These results started by
identifying configurations which characterize minimal energy, then led to
Lifshitz tail bounds on the integrated density of states as well as a Wegner
estimate near the spectral minimum, which ultimately resulted in a proof of
spectral and dynamical localization at low energy for the multi-dimensional
random displacement model.Comment: 31 pages, 7 figures, final version, to appear in Proceedings of
"Spectral Days 2010", Santiago, Chile, September 20-24, 201
PT-symetrically regularized Eckart,Poeschl-Teller and Hulthen potentials
Version 1: The well known Eckart's singular s-wave potential is
PT-symmetrically regularized and continued to the whole real line. The new
model remains exactly solvable and its bound states remain proportional to
Jacobi polynomials. Its real and discrete spectrum exhibits several unusual
features.
Version 2: Parity times time-reversal symmetry of complex Hamiltonians with
real spectra is usually interpreted as a weaker mathematical substitute for
Hermiticity. Perhaps an equally important role is played by the related
strengthened analyticity assumptions. In a constructive illustration we
complexify a few potentials solvable only in s-wave. Then we continue their
domain from semi-axis to the whole axis and get the new exactly solvable
models. Their energies come out real as expected. The new one-dimensional
spectra themselves differ quite significantly from their s-wave predecessors.Comment: Original 10-page letter ``PT-symmetrized exact solution of the
singular Eckart oscillator" is extended to a full pape
Field demonstration of simultaneous wind and temperaturemeasurements from 5to50 km with a Na double-edge magneto-optic filter in a multi-frequency Doppler lidar
We report the first (to our knowledge) field demonstration of simultaneous wind and temperature measurements with a Na double-edge magneto-optic filter implemented in the receiver of a three-frequency Na Doppler lidar. Reliable winds and temperatures were obtained in the altitude range of 10-45 km with 1 km resolution and 60 min integration under the conditions of 0.4 W lidar power and 75 cm telescope aperture. This edge filter with a multi-frequency lidar concept can be applied to other direct-detection Doppler lidars for profiling both wind and temperature simultaneously from the lower to the upper atmosphere
The melanoma-specific graded prognostic assessment does not adequately discriminate prognosis in a modern population with brain metastases from malignant melanoma
The melanoma-specific graded prognostic assessment (msGPA) assigns patients with brain metastases from malignant melanoma to 1 of 4 prognostic groups. It was largely derived using clinical data from patients treated in the era that preceded the development of newer therapies such as BRAF, MEK and immune checkpoint inhibitors. Therefore, its current relevance to patients diagnosed with brain metastases from malignant melanoma is unclear. This study is an external validation of the msGPA in two temporally distinct British populations.Performance of the msGPA was assessed in Cohort I (1997-2008, n=231) and Cohort II (2008-2013, n=162) using Kaplan-Meier methods and Harrell's c-index of concordance. Cox regression was used to explore additional factors that may have prognostic relevance.The msGPA does not perform well as a prognostic score outside of the derivation cohort, with suboptimal statistical calibration and discrimination, particularly in those patients with an intermediate prognosis. Extra-cerebral metastases, leptomeningeal disease, age and potential use of novel targeted agents after brain metastases are diagnosed, should be incorporated into future prognostic models.An improved prognostic score is required to underpin high-quality randomised controlled trials in an area with a wide disparity in clinical care
An approach to estimating prognosis using fractional polynomials in metastatic renal carcinoma
We present a prognostic model for metastatic renal cell carcinoma based on fractional polynomials. We retrospectively analysed 425 metastatic renal cell carcinoma patients treated with subcutaneous recombinant cytokine-based home therapies in consecutive trials. In our approach, we categorised a continuous prognostic index produced by the multivariable fractional polynomial (MFP) algorithm, using a strategy in which continuous predictors are kept continuous. The MFP algorithm selected five prognostic factors as significant at the 5% level in a multivariable model: lymph node metastases, liver metastases, bone metastases, age, C-reactive protein and neutrophils. The MFP model allowed us to divide patients into four risk groups achieving median overall survivals of 38 months (low risk), 23 months (low intermediate risk), 15 months (high intermediate risk) and 5.6 months (high risk). Our approach, based on categorising a continuous prognostic index produced by the MFP algorithm, allowed more flexibility in the determination of risk groups than traditional approaches
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